Clinical Audit: Management of Acute Severe Asthma in West Glasgow
Bibliographic record
Abstract
BACKGROUND: The U.K. has 75,000 hospital admissions and over 1500 deaths from asthma annually. The British Thoracic Society (BTS) guidelines represent the recognised standard for acute asthma management. We assessed the degree of conformity with these guidelines in an acute medical unit. METHODOLOGY: Data from consecutive admissions were collected prospectively. Practice was audited in October December 2005 and October 2006 - January 2007. Between cycles an educational programme was instigated, RESULTS: Fifty-eight patients were included. Clinical parameters were well recorded in both cycles. Peak expiratory flow was consistently under-recorded (72% at admission; 67% in monitoring). in monitoring). Severity assessment was documented at 55% and 66% in cycle one and two respectively. Of these, the assessment was incorrect in 33% in cycle one and 21% in cycle two. All misclassifications of severity were underestimates. All life-threatening attacks were not identified. No improvement occurred between cycles. Overall, 60% of patients were inappropriately treated according to BTS guidelines, 40% due to under-treatment. Under-treatment occurred more frequently in cycle two compared with cycle one (57% vs. 24%, p = 0.007), predominantly due to inadequate treatment of life-threatening asthma. CONCLUSION: Management of acute asthma in a large, urban teaching hospital is suboptimal. Educational intervention failed to improve care; more comprehensive strategies are required.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".